[LTA-RDG] SENIOR/ DATA SCIENTIST

Job description

[What the role is] SENIOR DATA SCIENTIST [What you will be working on] The Rail Digitalisation Division is a cross-functional and multi-disciplinary team set up to drive and deliver LTA’s Railway Common Data Platform (CDP) , which includes data analytics and artificial intelligence capabilities to support rail performance and operational/maintenance enhancements. You will be responsible for building the "intelligence layer" of the CDP, developing systems that not only detect anomalies in complex railway time-series data but also reason about them to provide clear, actionable outcomes for maintenance and operations. We are seeking a Senior Data Scientist who excels at converting use cases into a data problem and analyzing data to generate value to support decision making. You should have a proven track record of delivering end-to-end machine learning solutions—from data discovery and feature engineering to model deployment and monitoring. The ideal candidate balances deep technical expertise with a value-driven mindset, ensuring that analytical outputs directly translate to better cost efficiency and improved commuter experience. A degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field is required. Technical Skills Modeling & Time-Series Analysis: Expert proficiency in Python and SQL. Deep experience in time-series forecasting and anomaly detection (e.g., Z-score, growth rate analysis, and statistical thresholds). Data Engineering Synergy: Competence with modern data stacks (e.g., Snowflake, Databricks ) and real-time data ingestion via APIs to build scalable, production-ready pipelines. MLOps & Automation: Experience in managing the full ML lifecycle, focusing on "operational AI" that triggers automated workflows or maintenance alerts. Visualization & UI Collaboration: Ability to translate complex model outputs into requirements for UI/UX designers to create intuitive, data-rich enterprise dashboards. Decision Intelligence: Proven ability to build autonomous systems that go beyond simple detection, including experience with AI agents that combine statistical triggers with LLM-based reasoning to automatically categorise, prioritise, and/or escalate operational issues. Key Attributes Analytical Problem Solver: Strong ability to take vague operational "pain points" and structure them into rigorous analytical frameworks that drive ROI. Stakeholder Management: Exceptional communication skills to explain algorithmic logic and "uncertainty" to non-technical stakeholders. Proactive Learner: A self-starter who stays updated on the latest in Agentic AI and can independently drive design initiatives end-to-end. Collaborative: High comfort level working in a "squad" format alongside UI/UX designers, Product Managers, and Railway Engineers. [What we are looking for] Background knowledge in Computer Engineering, Data Science, Statistics, Computer Science, Engineering, or a related quantitative field is required. Technical Skills At least 5 years of relevant experience in data science, preferably with data-heavy industrial or enterprise products. Experience in transportation, IoT, or large-scale condition-monitoring systems with AI agents is advantageous. Successful candidates may be expected to undertake technical assessments or case study presentations as part of the interview process.